The expected increase in the number of Telematics applications by MTUs used with off-board or on-board route guidance as well as the increase in the number of CNS users would increase the percentage of vehicles that would use Dynamic Route Guidance and would hence result in unpredicted changes in traffic load which has the potential to cause erratic traffic.
Traditional traffic predictions could use a database of consistent traffic in order to predict traffic according to expected traffic loads, possibly also according to prior knowledge about the behavior of the traffic and the current conditions of traffic. However DRG effects on traffic might mostly be unpredictable by such a database. This could be the result even though there is a priori information about off board DRG (routs plans provided by common service centers), since deviations in the schedule of routes and possible use of alternative routes could in a short time make prior knowledge to become irrelevant to traffic prediction. Thus it would be valuable to have a means to update a traffic database that would be used in conjunction with consistent traffic information and possibly with other prior knowledge including current traffic information in order to improve the capability to predict potential changes in traffic.
Consistent Traffic is defined as such traffic that has a repetitive characteristic, with respect to specific time periods and places, (e.g. certain hour in a certain day of the week in a certain road). Consistent Traffic is a result of behavior patterns that from a statistical point of view usually and in general may be characterized. Such traffic characteristics may be stored in an off-line data base which may contribute to traffic predictions.
Inconsistent Traffic is defined as such traffic that has a non repetitive and erratic characteristic with respect to specific time periods and places. Such traffic may for example be the result of the ability by the individual driver to change routes according to current traffic loads. As the number of drivers that have access to detailed information on currently changing traffic increases, and as the number of drivers that possess in-car sophisticated capability to individually vary their previous route plans, and the less coordination if any exists amongst various drivers, the more inconsistent would become such traffic. Inconsistent Traffic is difficult if at all possible to be characterized on a statistical basis. Such traffic tends to be in general unpredictable, and leads to unpredictable traffic loads.
The inconsistent traffic is expected to become a significant issue in the control of the traffic when a significant percentage of cars will be using dynamic route guidance and as a result might probably, in themselves cause unexpected traffic loads at certain places that would affect the traffic and reduce the efficiency of dynamic route guidance. Traffic information used with Dynamic Route Guidance (DRG) could be one reason for the inconsistency in the traffic due to changes in planned routes, while driver preferences, deviation from schedule, or reaction to local based services could be other causes for an inconsistency in the conditions of the traffic.
One general approach to resolve the problem of predicting inconsistent traffic is to centralize the control of the individual driver routes. This is not the approach which is considered in the following embodiment of the invention as it leads to centralized DRG which has many disadvantages beside feasibility problems with large scale implementation.
As further explained, apart from the contribution of traffic predictions of inconsistent traffic to traffic control the predictions could further lead to a relatively low cost implementation of an anonymous predictive DRG approach based on distributed intelligence of the in car computers and also to contribute to the implementation of more efficient telematics applications.
Predictions for inconsistent traffic is based on a process of traffic load estimation for predetermined place and time interval, (for example, estimating the number of vehicles that use in-car navigation computers which are expected to pass in a certain road in a certain forward time interval). However when the source of such information is limited to car navigation units that use dynamic route guidance only, and the estimation process is the only means for such predictions, it would be required that most of the cars should use car navigation systems. In practice such a situation would doubtfully be viable. However, the situation when a significant percentage of vehicular systems would most probably be using Dynamic Route Guidance (DRG) may be considered realistic in the not too distant future, and hence inconsistent traffic would begin to appear at an early stage, whereas reliable traffic prediction for this situation would not yet be available. With the lack of traffic predictions, the problems that would be encountered at such stages could lead to a significant dilemma by the individual drivers, about the efficiency of Dynamic Route Guidance. The dilemma would be whether to consider recommended DRG according to current traffic, while ignoring unpredictable traffic that might result due to the significant number of DRG users, or ignoring the recommended DRG. For such early stages of inconsistent traffic the following embodiment suggests a modified method of traffic predictions in order to enable reliable prediction at such early stages. Traffic load predictions would preferably refer mostly to sensitive roads that encounter recurrent traffic jams.